Directed Evolution Reveals the Functional Sequence Space of an Adenylation Domain Specificity Code

Viral escape-inspired framework for structure-guided dual bait protein biosensor design

A generalizable computational platform, CTRL-V (Computational TRacking of Likely Variants), is introduced to design selective binding (dual bait) biosensor proteins. The iteratively evolving receptor binding domain (RBD) of SARS-CoV-2 spike protein has been construed as a model dual bait biosensor which has iteratively evolved to distinguish and selectively bind to human entry receptors and avoid binding neutralizing antibodies. Spike RBD prioritizes mutations that reduce antibody binding while enhancing/ retaining binding with the ACE2 receptor. CTRL-V's through iterative design cycles was shown to pinpoint 20% (of the 39) reported SARS-CoV-2 point mutations across 30 circulating, infective strains as responsible for immune escape from commercial antibody LY-CoV1404. CTRL-V successfully identifies ~70% (five out of seven) single point mutations (371F, 373P, 440K, 445H, 456L) in the latest circulating KP.2 variant and offers detailed structural insights to the escape mechanism. While other data-driven viral escape variant predictor tools have shown promise in predicting potential future viral variants, they require massive amounts of data to bypass the need for physics of explicit biochemical interactions. Consequently, they cannot be generalized for other protein design applications. The publicly availably viral escape data was leveraged as in vivo anchors to streamline a computational workflow that can be generalized for dual bait biosensor design tasks as exemplified by identifying key mutational loci in Raf kinase that enables it to selectively bind Ras and Rap1a GTP. We demonstrate three versions of CTRL-V which use a combination of integer optimization, stochastic sampling by PyRosetta, and deep learning-based ProteinMPNN for structure-guided biosensor design.

Directed Evolution of an Adenylation Domain Alters Substrate Specificity and Generates a New Catechol Siderophore in Escherichia coli

Nonribosomal peptide synthetases (NRPS) biosynthesize numerous natural products with therapeutic, agricultural, and industrial significance. Reliably altering substrate selection in these enzymes has been a longstanding goal, as this would enable the production of tailor-made peptides with desired activities. In this study, the NRPS EntF and the associated biosynthesis of the siderophore enterobactin (ENT) were used as a model system to interrogate substrate selection by an adenylation (A) domain. We employed a directed evolution pipeline that harnesses an in vivo genetic selection for siderophore production to alter A domain substrate selection. Surprisingly, this led to the formation of a new, physiologically active catechol siderophore in Escherichia coli. We characterized the enzyme variants in vitro and demonstrated transferability of our findings to the well-studied TycC and GrsB NRPSs. This work identifies critical binding pocket residues that allow for altered substrate selection in our model system and expands upon our understanding of iron acquisition in E. coli.

Functional Diversity and Engineering of the Adenylation Domains in Nonribosomal Peptide Synthetases

Nonribosomal peptides (NRPs) are biosynthesized by nonribosomal peptide synthetases (NRPSs) and are widely distributed in both terrestrial and marine organisms. Many NRPs and their analogs are biologically active and serve as therapeutic agents. The adenylation (A) domain is a key catalytic domain that primarily controls the sequence of a product during the assembling of NRPs and thus plays a predominant role in the structural diversity of NRPs. Engineering of the A domain to alter substrate specificity is a potential strategy for obtaining novel NRPs for pharmaceutical studies. On the basis of introducing the catalytic mechanism and multiple functions of the A domains, this article systematically describes several representative NRPS engineering strategies targeting the A domain, including mutagenesis of substrate-specificity codes, substitution of condensation-adenylation bidomains, the entire A domain or its subdomains, domain insertion, and whole-module rearrangements.

Structural, biochemical and bioinformatic analyses of nonribosomal peptide synthetase adenylation domains

Covering: 1997 to July 2023The adenylation reaction has been a subject of scientific intrigue since it was first recognized as essential to many biological processes, including the homeostasis and pathogenicity of some bacteria and the activation of amino acids for protein synthesis in mammals. Several foundational studies on adenylation (A) domains have facilitated an improved understanding of their molecular structures and biochemical properties, in particular work on nonribosomal peptide synthetases (NRPSs). In NRPS pathways, A domains activate their respective acyl substrates for incorporation into a growing peptidyl chain, and many nonribosomal peptides are bioactive. From a natural product drug discovery perspective, improving existing bioinformatics platforms to predict unique NRPS products more accurately from genomic data is desirable. Here, we summarize characterization efforts of A domains primarily from NRPS pathways from July 1997 up to July 2023, covering protein structure elucidation, in vitro assay development, and in silico tools for improved predictions.

Current status and emerging frontiers in enzyme engineering: An industrial perspective

Protein engineering mechanisms can be an efficient approach to enhance the biochemical properties of various biocatalysts. Immobilization of biocatalysts and the introduction of new-to-nature chemical reactivities are also possible through the same mechanism. Discovering new protocols that enhance the catalytic active protein that possesses novelty in terms of being stable, active, and, stereoselectivity with functions could be identified as essential areas in terms of concurrent bioorganic chemistry (synergistic relationship between organic chemistry and biochemistry in the context of enzyme engineering). However, with our current level of knowledge about protein folding and its correlation with protein conformation and activities, it is almost impossible to design proteins with specific biological and physical properties. Hence, contemporary protein engineering typically involves reprogramming existing enzymes by mutagenesis to generate new phenotypes with desired properties. These processes ensure that limitations of naturally occurring enzymes are not encountered. For example, researchers have engineered cellulases and hemicellulases to withstand harsh conditions encountered during biomass pretreatment, such as high temperatures and acidic environments. By enhancing the activity and robustness of these enzymes, biofuel production becomes more economically viable and environmentally sustainable. Recent trends in enzyme engineering have enabled the development of tailored biocatalysts for pharmaceutical applications. For instance, researchers have engineered enzymes such as cytochrome P450s and amine oxidases to catalyze challenging reactions involved in drug synthesis. In addition to conventional methods, there has been an increasing application of machine learning techniques to identify patterns in data. These patterns are then used to predict protein structures, enhance enzyme solubility, stability, and function, forecast substrate specificity, and assist in rational protein design. In this review, we discussed recent trends in enzyme engineering to optimize the biochemical properties of various biocatalysts. Using examples relevant to biotechnology in engineering enzymes, we try to expatiate the significance of enzyme engineering with how these methods could be applied to optimize the biochemical properties of a naturally occurring enzyme.

Analysing Megasynthetase Mutants at High Throughput Using Droplet Microfluidics

Nonribosomal peptide synthetases (NRPSs) are giant enzymatic assembly lines that deliver many pharmaceutically valuable natural products, including antibiotics. As the search for new antibiotics motivates attempts to redesign nonribosomal metabolic pathways, more robust and rapid sorting and screening platforms are needed. Here, we establish a microfluidic platform that reliably detects production of the model nonribosomal peptide gramicidin S. The detection is based on calcein-filled sensor liposomes yielding increased fluorescence upon permeabilization. From a library of NRPS mutants, the sorting platform enriches the gramicidin S producer 14.5-fold, decreases internal stop codons 250-fold, and generates enrichment factors correlating with enzyme activity. Screening for NRPS activity with a reliable non-binary sensor will enable more sophisticated structure-activity studies and new engineering applications in the future.

Advances in the adenylation domain: discovery of diverse non-ribosomal peptides

Non-ribosomal peptide synthetases are mega-enzyme assembly lines that synthesize many clinically useful compounds. As a gatekeeper, they have an adenylation (A)-domain that controls substrate specificity and plays an important role in product structural diversity. This review summarizes the natural distribution, catalytic mechanism, substrate prediction methods, and in vitro biochemical analysis of the A-domain. Taking genome mining of polyamino acid synthetases as an example, we introduce research on mining non-ribosomal peptides based on A-domains. We discuss how non-ribosomal peptide synthetases can be engineered based on the A-domain to obtain novel non-ribosomal peptides. This work provides guidance for screening non-ribosomal peptide-producing strains, offers a method to discover and identify A-domain functions, and will accelerate the engineering and genome mining of non-ribosomal peptide synthetases. KEY POINTS: • Introducing adenylation domain structure, substrate prediction, and biochemical analysis methods • Advances in mining homo polyamino acids based on adenylation domain analysis • Creating new non-ribosomal peptides by engineering adenylation domains.

Structural Organization of Brevilaterin Biosynthesis in Brevibacillus laterosporus S62-9: A Novel MbtH-Independent Cationic Antimicrobial Peptide Synthetase System

Cationic antimicrobial peptides, produced by nonribosomal peptide synthetases (NRPSs), have received great attention in different applications, including as biocontrol and antimicrobial agents against foodborne pathogenic bacteria. Also, Brevibacillus spp. is a competent microorganism to produce cationic antimicrobial peptides yet has received little attention. Herein, Brevibacillus laterosporus S62-9 genome mining revealed an integrated cationic antimicrobial peptide synthetase system that synthesized brevilaterin. Combining biochemical analysis with bioinformatics elucidated that the A domain from this system was the MbtH-independent enzyme and showed activity against the same amino acid in the structure of brevilaterin. Moreover, the creations of the first three and position 12 residues in the sequence were targeted to bre261, bre270, bre2691A, and bre2662, respectively. Further analysis of the specificity-conferring code of the A domain suggested that a tiny difference would make the activity of the A domain very diverse and the range of substrate selection would be enlarged or narrowed by changing some residues in the code. The dissection of this biosynthesis mechanism would contribute to the successful realization of reasonable artificial design and the modification of bioactive peptides, and this capable organism also would be more fully utilized.

Design of novel enzyme biocatalysts for industrial bioprocess: Harnessing the power of protein engineering, high throughput screening and synthetic biology

Biocatalysts have wider applications in various industries. Biocatalysts are generating bigger attention among researchers due to their unique catalytic properties like activity, specificity and stability. However the industrial use of many enzymes is hindered by low catalytic efficiency and stability during industrial processes. Properties of enzymes can be altered by protein engineering. Protein engineers are increasingly study the structure-function characteristics, engineering attributes, design of computational tools for enzyme engineering, and functional screening processes to improve the design and applications of enzymes. The potent and innovative techniques of enzyme engineering deliver outstanding opportunities for tailoring industrially important enzymes for the versatile production of biochemicals. An overview of the current trends in enzyme engineering is explored with important representative examples.

Biosynthetic Functionalization of Nonribosomal Peptides

Nonribosomal peptides (NRPs) are a therapeutically important class of secondary metabolites that are produced by modular synthetases in assembly-line fashion. We previously showed that a single Trp-to-Ser mutation in the initial Phe-loading adenylation domain of tyrocidine synthetase completely switches the specificity toward clickable analogues. Here we report that this minimally invasive strategy enables efficient functionalization of the bioactive NRP on the pathway level. In a reconstituted tyrocidine synthetase, the W227S point mutation permitted selective incorporation of Phe analogues with alkyne, halogen, and benzoyl substituents by the initiation module. The respective W2742S mutation in module 4 similarly permits efficient incorporation of these functionalized substrate analogues at position 4, expanding this strategy to elongation modules. Efficient incorporation of an alkyne handle at position 1 or 4 of tyrocidine A allowed site-selective one-step fluorescent labeling of the corresponding tyrocidine analogues by Cu(I)-catalyzed alkyne-azide cycloaddition. By combining synthetic biology with bioorthogonal chemistry, this approach holds great potential for NRP isolation and molecular target elucidation as well as combinatorial optimization of NRP therapeutics.

Protein engineering for natural product biosynthesis and synthetic biology applications

As protein engineering grows more salient, many strategies have emerged to alter protein structure and function, with the goal of redesigning and optimizing natural product biosynthesis. Computational tools, including machine learning and molecular dynamics simulations, have enabled the rational mutagenesis of key catalytic residues for enhanced or altered biocatalysis. Semi-rational, directed evolution and microenvironment engineering strategies have optimized catalysis for native substrates and increased enzyme promiscuity beyond the scope of traditional rational approaches. These advances are made possible using novel high-throughput screens, including designer protein-based biosensors with engineered ligand specificity. Herein, we detail the most recent of these advances, focusing on polyketides, non-ribosomal peptides and isoprenoids, including their native biosynthetic logic to provide clarity for future applications of these technologies for natural product synthetic biology.

Combinatorial biosynthesis for the generation of new-to-nature peptide antimicrobials

Natural peptide products are a valuable source of important therapeutic agents, including antibiotics, antivirals and crop protection agents. Aided by an increased understanding of structure-activity relationships of these complex molecules and the biosynthetic machineries that produce them, it has become possible to re-engineer complete machineries and biosynthetic pathways to create novel products with improved pharmacological properties or modified structures to combat antimicrobial resistance. In this review, we will address the progress that has been made using non-ribosomally produced peptides and ribosomally synthesized and post-translationally modified peptides as scaffolds for designed biosynthetic pathways or combinatorial synthesis for the creation of novel peptide antimicrobials.

Engineering sensitivity and specificity of AraC-based biosensors responsive to triacetic acid lactone and orsellinic acid

We previously described the design of triacetic acid lactone (TAL) biosensor ‘AraC-TAL1’, based on the AraC regulatory protein. Although useful as a tool to screen for enhanced TAL biosynthesis, this variant shows elevated background (leaky) expression, poor sensitivity and relaxed inducer specificity, including responsiveness to orsellinic acid (OA). More sensitive biosensors specific to either TAL or OA can aid in the study and engineering of polyketide synthases that produce these and similar compounds. In this work, we employed a TetA-based dual-selection to isolate new TAL-responsive AraC variants showing reduced background expression and improved TAL sensitivity. To improve TAL specificity, OA was included as a ‘decoy’ ligand during negative selection, resulting in the isolation of a TAL biosensor that is inhibited by OA. Finally, to engineer OA-specific AraC variants, the iterative protein redesign and optimization computational framework was employed, followed by 2 rounds of directed evolution, resulting in a biosensor with 24-fold improved OA/TAL specificity, relative to AraC-TAL1.

Redesign of Substrate Selection in Glycopeptide Antibiotic Biosynthesis Enables Effective Formation of Alternate Peptide Backbones

Nonribosomal peptide synthesis is capable of utilizing a wide range of amino acid residues due to the selectivity of adenylation (A)-domains. Changing the selectivity of A-domains could lead to new bioactive nonribosomal peptides, although remodeling efforts of A-domains are often unsuccessful. Here, we explored and successfully reengineered the specificity of the module 3 A-domain from glycopeptide antibiotic biosynthesis to change the incorporation of 3,5-dihydroxyphenylglycine into 4-hydroxyphenylglycine. These engineered A-domains remain selective in a functioning peptide assembly line even under substrate competition conditions and indicate a possible application of these for the future redesign of GPA biosynthesis.

HAMA: a multiplexed LC-MS/MS assay for specificity profiling of adenylate-forming enzymes

Adenylation enzymes are engineering targets in ribosomal and nonribosomal peptide synthesis. Through multiplexed LC-MS/MS measurement of hydroxamates, the HAMA assay records specificity profiles of these enzymes in a snap.

Adenylation enzymes selecting substrates for ribosomal and nonribosomal protein and peptide biosynthesis have been popular targets of enzyme engineering. Previous standard assays for adenylation specificity have been cumbersome and failed to reflect the competition conditions inside a cell because they measure substrates one at a time. We have developed an adenylation assay based on hydroxamate quenching and LC-MS/MS detection of hydroxamate products testing dozens of competing amino acid substrates in parallel. Streamlined specificity profiling of adenylation enzymes will facilitate engineering and directed evolution of ribosomal and nonribosomal peptide synthesis.